crowwork has posted 2 projects.


Logo XGBoost v0.2

by crowwork - May 17, 2014, 07:27:59 CET [ Project Homepage BibTeX Download ] 1668 views, 277 downloads, 1 subscription

About: eXtreme gradient boosting (tree) library. Features: - Sparse feature format allows easy handling of missing values, and improve computation efficiency. - Efficient parallel implementation that optimizes memory and computation. - Python interface

Changes:

New features: - Python interface - New objectives: weighted training, pairwise rank, multiclass softmax - Comes with example script on Kaggle Higgs competition, 20 times faster than skilearn's GBRT


About: SVDFeature is a toolkit for developing generic collaborative filtering algorithms by defining features.

Changes:

JMLR MLOSS version.